Feast project
foundation · United StatesScores
1 product on the map — 1 open.
Openness
5 high confidence- license
- Apache-2.0(OSI)
- source
- public
- core features withheld
- no
Apache-2.0 license body confirmed. The repository is public and unarchived and builds the whole product, and the README describes no paid tier, enterprise edition or license-gated build beside it, so source is public and the core ungated.
- https://raw.githubusercontent.com/feast-dev/feast/master/LICENSE recorded 2026-09-30
LICENSE file is the Apache-2.0 text: "Apache License" and "Version 2.0, January 2004" and "TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION".
- https://raw.githubusercontent.com/feast-dev/feast/master/README.md recorded 2026-09-30
README shows the "Apache%202.0" badge and describes Feast as providing "a single data access layer that abstracts feature storage from feature retrieval"; searched the body for enterprise, paid tier, license key and commercial: none.
Adoption
3 high confidencePyPI downloads of feast drive this reading, since that package is the channel Feast declares for distribution. The figure therefore measures use of the tool itself, not a proxy for it.
- https://pypistats.org/api/packages/feast/recent recorded 2026-08-18
last_month downloads = 724,047 for feast
Capability
3 medium confidenceFeast orchestrates point-in-time-correct offline retrieval, online serving and materialization across pluggable stores, with a feature registry. Its alpha vector search calls into a separate vector store rather than providing an index of its own, which keeps it two steps below Vespa, a complete distributed retrieval system.
- https://raw.githubusercontent.com/feast-dev/feast/master/docs/reference/alpha-vector-database.md recorded 2026-09-30
Alpha vector database page says "Feast provides general APIs to store and retrieve embeddings." and lists Pgvector, Elasticsearch, Milvus, Qdrant and ScyllaDB as supported vector databases.
- https://raw.githubusercontent.com/feast-dev/feast/master/README.md recorded 2026-09-30
README describes Feast as helping teams "Make features consistently available for training and serving" by managing an offline store, an online store and a feature server.